Sell-Through Rate: Formula,
Benchmarks & How to Improve It
Sell-through rate measures how much of the stock you received actually sold in a period. The formula, sensible benchmarks by context, why a weekly cadence beats a monthly one, and how to lift the number without gutting your margin.
By Replenagise · Updated 11 July 2026 · 5 min read
What is sell-through rate — and the formula
Sell-Through Rate (%) = Units Sold ÷ Units Received × 100, measured over the same period.
Receive 200 units at the start of the month and sell 130 of them: sell-through is 65%. Unlike stock counts, sell-through judges the buy — it tells you whether the quantity you brought in matched the demand that actually showed up. Run it per SKU and per channel and it becomes the earliest honest signal you get: winners sell through fast and ask for a reorder; losers sit at 20% and volunteer for the markdown list before they harden into dead stock.
Reading the number: benchmarks & cadence
What “good” looks like
There is no universal benchmark, but useful working ranges: 70–90% over a season for fashion/seasonal buys, 40–60% monthly for stable replenishable lines. Persistent 90%+ usually means you under-bought and left sales on the table.
Low sell-through, fast response
A SKU at 15–25% a few weeks after intake is telling you the price, the listing, or the demand read was wrong. Respond while the season can still absorb a fix — markdown, bundle, or channel switch.
Weekly beats monthly
A monthly number arrives after the correction window has closed. Weekly sell-through per SKU catches a stalling line in week two, when a small promo still fixes it — not in week six, when only a clearance will.
Per channel, not just per SKU
The same product can run 80% on Amazon and 25% on your Shopify store. Channel-level sell-through shows where the demand actually is — and where stock should be moved, not just marked down.
How to improve sell-through — and how Replenagise tracks it
Lifting sell-through is either a demand fix (better listings, price moves, promotion, switching the stock to the channel where it sells) or a buying fix (smaller, more frequent orders sized to forecast demand rather than supplier optimism). The second is quieter and usually worth more: every over-buy you avoid is sell-through you never have to rescue.
Replenagise gives you both sides: stock velocity and sell-through reporting per SKU, per channel, and per store — synced live from Shopify and Linnworks — plus forecasts that size the next purchase order to what demand actually supports. The result is fewer heroic markdowns, because fewer buys need rescuing.
Related reading: what happens when sell-through stays low — dead stock — the companion metric days of inventory on hand, and the inventory forecasting software that keeps buys honest.
Sell-Through Rate — FAQs
How do you calculate sell-through rate?
Divide units sold by units received over the same period and multiply by 100. Receive 200, sell 130 → 65% sell-through. Measure per SKU and per channel for numbers you can act on; blended totals hide both the winners and the problems.
What is a good sell-through rate?
Context decides. Seasonal and fashion buys typically target 70–90% across the season; stable replenishable lines often sit at 40–60% per month, since you deliberately hold cover stock. Consistently above 90% suggests under-buying — you are stocking out of winners.
What is the difference between sell-through and inventory turnover?
Sell-through compares sales to what you received in a period — it judges a specific buy. Inventory turnover compares annual sales (at cost) to average stock held — it judges the whole system. Use sell-through to fix this month’s decisions, turnover to track the year.
How do I track sell-through automatically?
Replenagise reports sell-through and stock velocity per SKU, channel, and store from live Shopify and Linnworks data — no exports or spreadsheet builds. Slow lines surface early, and the same data drives forecasts so the next buy is sized to real demand.
See Your Sell-Through by SKU, Channel & Store
Live sell-through and velocity reporting, with forecasts that size the next order to real demand — for Shopify and Linnworks.